Peer effects in computer assisted learning: evidence from a randomized experiment

Marcel Fafchamps and Di Mo ()
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Di Mo: Stanford University and REAP

Experimental Economics, 2018, vol. 21, issue 2, No 6, 355-382

Abstract: Abstract We conduct a large scale experiment to investigate peer effects in computer assisted learning (CAL). Identification relies on three levels of randomization. We find an average 0.17 standard deviation improvement in math scores among primary school students. This average effect is the same for students treated individually or in pairs, implying that peer effects double the learning benefit from a given equipment. Among paired students, poor performers benefit more from CAL when paired with good performers and vice versa. Average performers benefit equally irrespective of who they are paired with. This suggests that the treatment is dominated by knowledge exchange between peers. We also find that CAL treatment reduces the dispersion in math scores and that the beneficial effects of CAL can be strengthened if weak students are systematically paired with strong students.

Keywords: Peer effects; Pairing; Math performance; Dispersion (search for similar items in EconPapers)
JEL-codes: B4 I2 J0 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (5)

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Related works:
Working Paper: Peer Effects in Computer Assisted Learning: Evidence from a Randomized Experiment (2017)
Working Paper: Peer Effects in Computer Assisted Learning: Evidence from a Randomized Experiment (2015)
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DOI: 10.1007/s10683-017-9538-z

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